{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "22ed8108",
   "metadata": {},
   "source": [
    "# DAY6 数据可视化\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f2289687",
   "metadata": {},
   "source": [
    "之前已经说过，对于数据可视化一般会进行如下操作\n",
    "1. 单特征分布可视化\n",
    "2. 特征与标签关系可视化\n",
    "3. 特征与特征关系可视化"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "75898881",
   "metadata": {},
   "source": [
    "## 单特征分布可视化"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2de93e1e",
   "metadata": {},
   "source": [
    "### 找到连续特征"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "b052fe8b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Id</th>\n",
       "      <th>Home Ownership</th>\n",
       "      <th>Annual Income</th>\n",
       "      <th>Years in current job</th>\n",
       "      <th>Tax Liens</th>\n",
       "      <th>Number of Open Accounts</th>\n",
       "      <th>Years of Credit History</th>\n",
       "      <th>Maximum Open Credit</th>\n",
       "      <th>Number of Credit Problems</th>\n",
       "      <th>Months since last delinquent</th>\n",
       "      <th>Bankruptcies</th>\n",
       "      <th>Purpose</th>\n",
       "      <th>Term</th>\n",
       "      <th>Current Loan Amount</th>\n",
       "      <th>Current Credit Balance</th>\n",
       "      <th>Monthly Debt</th>\n",
       "      <th>Credit Score</th>\n",
       "      <th>Credit Default</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>Own Home</td>\n",
       "      <td>482087.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>26.3</td>\n",
       "      <td>685960.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>debt consolidation</td>\n",
       "      <td>Short Term</td>\n",
       "      <td>99999999.0</td>\n",
       "      <td>47386.0</td>\n",
       "      <td>7914.0</td>\n",
       "      <td>749.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>Own Home</td>\n",
       "      <td>1025487.0</td>\n",
       "      <td>10+ years</td>\n",
       "      <td>0.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>15.3</td>\n",
       "      <td>1181730.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>debt consolidation</td>\n",
       "      <td>Long Term</td>\n",
       "      <td>264968.0</td>\n",
       "      <td>394972.0</td>\n",
       "      <td>18373.0</td>\n",
       "      <td>737.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2</td>\n",
       "      <td>Home Mortgage</td>\n",
       "      <td>751412.0</td>\n",
       "      <td>8 years</td>\n",
       "      <td>0.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>35.0</td>\n",
       "      <td>1182434.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>debt consolidation</td>\n",
       "      <td>Short Term</td>\n",
       "      <td>99999999.0</td>\n",
       "      <td>308389.0</td>\n",
       "      <td>13651.0</td>\n",
       "      <td>742.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3</td>\n",
       "      <td>Own Home</td>\n",
       "      <td>805068.0</td>\n",
       "      <td>6 years</td>\n",
       "      <td>0.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>22.5</td>\n",
       "      <td>147400.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>debt consolidation</td>\n",
       "      <td>Short Term</td>\n",
       "      <td>121396.0</td>\n",
       "      <td>95855.0</td>\n",
       "      <td>11338.0</td>\n",
       "      <td>694.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4</td>\n",
       "      <td>Rent</td>\n",
       "      <td>776264.0</td>\n",
       "      <td>8 years</td>\n",
       "      <td>0.0</td>\n",
       "      <td>13.0</td>\n",
       "      <td>13.6</td>\n",
       "      <td>385836.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>debt consolidation</td>\n",
       "      <td>Short Term</td>\n",
       "      <td>125840.0</td>\n",
       "      <td>93309.0</td>\n",
       "      <td>7180.0</td>\n",
       "      <td>719.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Id Home Ownership  Annual Income Years in current job  Tax Liens  \\\n",
       "0   0       Own Home       482087.0                  NaN        0.0   \n",
       "1   1       Own Home      1025487.0            10+ years        0.0   \n",
       "2   2  Home Mortgage       751412.0              8 years        0.0   \n",
       "3   3       Own Home       805068.0              6 years        0.0   \n",
       "4   4           Rent       776264.0              8 years        0.0   \n",
       "\n",
       "   Number of Open Accounts  Years of Credit History  Maximum Open Credit  \\\n",
       "0                     11.0                     26.3             685960.0   \n",
       "1                     15.0                     15.3            1181730.0   \n",
       "2                     11.0                     35.0            1182434.0   \n",
       "3                      8.0                     22.5             147400.0   \n",
       "4                     13.0                     13.6             385836.0   \n",
       "\n",
       "   Number of Credit Problems  Months since last delinquent  Bankruptcies  \\\n",
       "0                        1.0                           NaN           1.0   \n",
       "1                        0.0                           NaN           0.0   \n",
       "2                        0.0                           NaN           0.0   \n",
       "3                        1.0                           NaN           1.0   \n",
       "4                        1.0                           NaN           0.0   \n",
       "\n",
       "              Purpose        Term  Current Loan Amount  \\\n",
       "0  debt consolidation  Short Term           99999999.0   \n",
       "1  debt consolidation   Long Term             264968.0   \n",
       "2  debt consolidation  Short Term           99999999.0   \n",
       "3  debt consolidation  Short Term             121396.0   \n",
       "4  debt consolidation  Short Term             125840.0   \n",
       "\n",
       "   Current Credit Balance  Monthly Debt  Credit Score  Credit Default  \n",
       "0                 47386.0        7914.0         749.0               0  \n",
       "1                394972.0       18373.0         737.0               1  \n",
       "2                308389.0       13651.0         742.0               0  \n",
       "3                 95855.0       11338.0         694.0               0  \n",
       "4                 93309.0        7180.0         719.0               0  "
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 首先查看都有什么特征\n",
    "import pandas as pd\n",
    "data = pd.read_csv('E:\\study\\PythonStudy\\python60-days-challenge-master\\data.csv')\n",
    "data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "756263c5",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['Id',\n",
       " 'Annual Income',\n",
       " 'Tax Liens',\n",
       " 'Number of Open Accounts',\n",
       " 'Years of Credit History',\n",
       " 'Maximum Open Credit',\n",
       " 'Number of Credit Problems',\n",
       " 'Months since last delinquent',\n",
       " 'Bankruptcies',\n",
       " 'Current Loan Amount',\n",
       " 'Current Credit Balance',\n",
       " 'Monthly Debt',\n",
       " 'Credit Score',\n",
       " 'Credit Default']"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 找到所有的连续特征，这是之前的写法\n",
    "continuous_features = []\n",
    "for i in data.columns:\n",
    "    if data[i].dtype != 'object':\n",
    "        continuous_features.append(i)\n",
    "continuous_features"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "ae75882a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['Id',\n",
       " 'Annual Income',\n",
       " 'Tax Liens',\n",
       " 'Number of Open Accounts',\n",
       " 'Years of Credit History',\n",
       " 'Maximum Open Credit',\n",
       " 'Number of Credit Problems',\n",
       " 'Months since last delinquent',\n",
       " 'Bankruptcies',\n",
       " 'Current Loan Amount',\n",
       " 'Current Credit Balance',\n",
       " 'Monthly Debt',\n",
       " 'Credit Score',\n",
       " 'Credit Default']"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 实际上，实现上述操作，更简单的方法如下，借助select_dtypes方法。\n",
    "continuous_features = data.select_dtypes(include=['float64', 'int64']).columns.tolist()\n",
    "continuous_features"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "69cd5270",
   "metadata": {},
   "source": [
    "这里我们思考一下，既然实现一个路径有很多方法，到底什么方法是最好的呢？\n",
    "\n",
    "如果你在执行复杂的项目，你需要考虑到内存管理、运行效率、算法负责度，甚至是代码美观性。\n",
    "\n",
    "但是目前你的目标就是达到目的即可，所以你应该用最简单最直观的方法，这便于你读者一眼知道你在做什么。也不要过于记忆太多新的函数加大自己的学习成本。\n",
    "\n",
    "所以这里我推荐第一种方法，但是你问ai 他会告诉你第二种，第二种能看懂即可\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "28af5100",
   "metadata": {},
   "source": [
    "### 初识matplotlib库"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "130afc33",
   "metadata": {},
   "source": [
    "作为一个朴素的人类，你觉得绘制一个图需要什么？\n",
    "1. 需要指定图的类型，比如折线图，散点图，柱状图等\n",
    "2. 需要指定图的坐标轴，比如x轴和y轴，并且传入数据\n",
    "3. 需要指定图的标题，比如x轴和y轴的标签，以及标题"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "d4609f6d",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "e:\\Anaconda\\envs\\vs\\Lib\\site-packages\\IPython\\core\\pylabtools.py:170: UserWarning: Glyph 30340 (\\N{CJK UNIFIED IDEOGRAPH-7684}) missing from font(s) DejaVu Sans.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "e:\\Anaconda\\envs\\vs\\Lib\\site-packages\\IPython\\core\\pylabtools.py:170: UserWarning: Glyph 31665 (\\N{CJK UNIFIED IDEOGRAPH-7BB1}) missing from font(s) DejaVu Sans.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "e:\\Anaconda\\envs\\vs\\Lib\\site-packages\\IPython\\core\\pylabtools.py:170: UserWarning: Glyph 32447 (\\N{CJK UNIFIED IDEOGRAPH-7EBF}) missing from font(s) DejaVu Sans.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "e:\\Anaconda\\envs\\vs\\Lib\\site-packages\\IPython\\core\\pylabtools.py:170: UserWarning: Glyph 22270 (\\N{CJK UNIFIED IDEOGRAPH-56FE}) missing from font(s) DejaVu Sans.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import seaborn as sns\n",
    "import matplotlib.pyplot as plt\n",
    "import pandas as pd\n",
    "\n",
    "\n",
    "sns.boxplot(x=data['Annual Income'])\n",
    "plt.title('Annual Income 的箱线图')\n",
    "plt.xlabel('Annual Income')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c4d82ae6",
   "metadata": {},
   "source": [
    "此时你会发现 \n",
    "1. 下方有莫名其妙的警告\n",
    "2. 中文字符显示不全"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "957078ac",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "import pandas as pd\n",
    "\n",
    "# 设置全局字体为支持中文的字体 (例如 SimHei)\n",
    "plt.rcParams['font.sans-serif'] = ['SimHei']\n",
    "# 解决负号'-'显示为方块的问题\n",
    "plt.rcParams['axes.unicode_minus'] = False\n",
    "\n",
    "sns.boxplot(x=data['Annual Income'])\n",
    "plt.title('年收入 箱线图')  # 使用中文标题\n",
    "plt.xlabel('年收入')      # 使用中文标签\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d906572e",
   "metadata": {},
   "source": [
    "数值变量有的是连续变量 有的是离散变量"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "8921a618",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 绘制直方图\n",
    "sns.histplot(data['Years in current job'])\n",
    "plt.title('在当前工作年限 直方图')\n",
    "plt.xlabel('在当前工作年限')\n",
    "plt.ylabel('员工数量')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "8d7327ef",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 还有很多新的参数可以调整图像 但是不需要记忆 用的时候问下ai即可\n",
    "sns.histplot(x=data['Years in current job'])\n",
    "plt.title('在当前工作年限 直方图')\n",
    "plt.xlabel('在当前工作年限')\n",
    "plt.ylabel('员工数量')\n",
    "plt.xticks(rotation=45, ha='right')  # 旋转45度，并右对齐\n",
    "plt.tight_layout()  # 自动调整子图参数，提供足够的空间\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "fb85a602",
   "metadata": {},
   "source": [
    "## 绘制特征和标签的关系"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "26496bc9",
   "metadata": {},
   "source": [
    "标签是离散的，特征如果是连续的应该绘制什么图？\n",
    "\n",
    "可以分别考虑违约和不违约情况下的连续特征，画2个箱线图\n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "5a97b8de",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 另一种可视化方式：箱线图\n",
    "plt.figure(figsize=(8, 6))\n",
    "sns.boxplot(x='Credit Default', y='Annual Income', data=data)\n",
    "plt.title('Annual Income vs. Credit Default')\n",
    "plt.xlabel('Credit Default')\n",
    "plt.ylabel('Annual Income')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "23c8f5c4",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 另一种可视化方式：小提琴图\n",
    "# 相较于箱线图，小提琴图更加美观\n",
    "plt.figure(figsize=(8, 6))\n",
    "sns.violinplot(x='Credit Default', y='Annual Income', data=data)\n",
    "plt.title('Annual Income vs. Credit Default')\n",
    "plt.xlabel('Credit Default')\n",
    "plt.ylabel('Annual Income')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8e34ccbb",
   "metadata": {},
   "source": [
    "但是实际上连续变量也可以绘制类似于直方图的图像，可以用核密度估计来完成边缘的柔和化"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "c1ea2b72",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 绘制 Annual Income 和 Credit Default 的关系图\n",
    "plt.figure(figsize=(8, 6))\n",
    "sns.histplot(x='Annual Income', hue='Credit Default', data=data, kde=True, element=\"step\")\n",
    "plt.title('Annual Income vs. Credit Default')\n",
    "plt.xlabel('Annual Income')\n",
    "plt.ylabel('Count')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3fd1c4d4",
   "metadata": {},
   "source": [
    "绘制离散变量和标签的关系"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "027faec3",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 绘制 Number of Open Accounts 和 Credit Default 的关系图\n",
    "plt.figure(figsize=(8, 6))\n",
    "sns.countplot(x='Number of Open Accounts', hue='Credit Default', data=data)\n",
    "plt.title('Number of Open Accounts vs. Credit Default')\n",
    "plt.xlabel('Number of Open Accounts')\n",
    "plt.ylabel('Count')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4e90ebf2",
   "metadata": {},
   "source": [
    "可以看到 如果number of open accounts的值太多 就会很散，不美观，所以这时候采取分组的措施"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "7a413265",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 将 \"Number of Open Accounts\" 分组\n",
    "data['Open Accounts Group'] = pd.cut(data['Number of Open Accounts'], bins=[0, 5, 10, 15, 20, float('inf')], labels=['0-5', '6-10', '11-15', '16-20', '20+']) # 根据你的数据调整分组\n",
    "\n",
    "plt.figure(figsize=(10, 6))\n",
    "sns.countplot(x='Open Accounts Group', hue='Credit Default', data=data)\n",
    "plt.title('Number of Open Accounts (Grouped) vs. Credit Default')\n",
    "plt.xlabel('Number of Open Accounts Group')\n",
    "plt.ylabel('Count')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6503739e",
   "metadata": {},
   "source": [
    "现在开始尝试对与其他的连续变量  离散变量都分别绘制 \n",
    "\n",
    "观察一下数据的特点，很多时候我们需要单纯从数据分布来认识数据，这才是真正有价值的事情。\n",
    "\n",
    "国内目前就有很有意思的现象：\n",
    "1. 科研界喜欢ai\n",
    "2. 政府政策相关研究讨厌ai\n",
    "\n",
    "\n",
    "是因为ai太浮于表面，很多时候不需要靠模型，单纯从数据上就可以得到很多有意思的结果。"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "vs",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.11.13"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}
